scholarly journals Towards Model-Driven Provisioning, Deployment, Monitoring, and Adaptation of Multi-cloud Systems

2013 ◽  
Author(s):  
Nicolas Ferry ◽  
Alessandro Rossini ◽  
Franck Chauvel ◽  
Brice Morin ◽  
Arnor Solberg
Keyword(s):  
Cloud Systems ◽  
Model Driven ◽  
Multi Cloud

Task scheduling algorithms for multi-cloud systems: allocation-aware approach

2017 ◽  
Vol 21 (2) ◽  
pp. 241-259 ◽  
Author(s):  
Sanjaya K. Panda ◽  
Indrajeet Gupta ◽  
Prasanta K. Jana
Keyword(s):  
Task Scheduling ◽  
Scheduling Algorithms ◽  
Cloud Systems ◽  
Multi Cloud

scholarly journals Allocation-aware Task Scheduling for Heterogeneous Multi-cloud Systems

2015 ◽  
Vol 50 ◽  
pp. 176-184 ◽  
Author(s):  
Sanjaya K. Panda ◽  
Indrajeet Gupta ◽  
Prasanta K. Jana
Keyword(s):  
Task Scheduling ◽  
Cloud Systems ◽  
Multi Cloud

scholarly journals Multi-Cloud Management Strategies for Simulating IoT Applications

2019 ◽  
Vol 24 (1) ◽  
pp. 83-103 ◽  
Author(s):  
András Márkus ◽  
József Dániel Dombi
Keyword(s):  
Management Strategies ◽  
Sensor Data ◽  
Smart Devices ◽  
Cloud Systems ◽  
Selection Strategies ◽  
Cloud Management ◽  
Cloud Technologies ◽  
The Internet Of Things ◽  
Multi Cloud ◽  
Application Execution

The Internet of Things (IoT) paradigm is closely coupled with cloud technologies, and the support for managing sensor data is one of the primary concerns of Cloud Computing. IoT-Cloud systems are widely used to manage sensors and different smart devices connected to the cloud, hence a large amount of data is generated by these things that need to be efficiently stored and processed. Simulation platforms have the advantage of enabling the investigation of complex systems without the need of purchasing and installing physical resources. In our previous work, we chose the DISSECT-CF simulator to model IoT-Cloud systems, and we also introduced provider policies to enable cost-aware policies resource management. The aim of this paper is to further extend the simulation capabilities of this tool by enabling multi-cloud management. In this paper we introduce four cloud selection strategies aimed to reduce application execution time and utilization costs. We detail our proposed method towards multi-cloud extension, and evaluate defined strategies through a meteorological application.

Middleware architecture for data consistency in multi-cloud systems

2021 ◽  
Vol 1 (2 (6)) ◽  
Author(s):  
Olha Kozina ◽  
Volodymyr Panchenko ◽  
Oleksandr Rysovanyi
Keyword(s):  
Resource Management ◽  
Service Provider ◽  
Cloud Service ◽  
Management Control ◽  
Data Consistency ◽  
Data Recording ◽  
Cloud Service Provider ◽  
Cloud Systems ◽  
Multi Cloud

Multi-cloud middleware must perform many different resource management, control, and monitoring functions that must interoperate but may differ in implementation in each cloud service provider. A mechanism for monotonic recording model implementation for multi-cloud systems with a geo-distributed middleware architecture is proposed in the article. It is shown, the middleware modules location defines the algorithm of synchronization of start moments of adjusting intervals required to generating the global sequence numbers for customer's data recording into the databases of multi-cloud systems. Figs.: 2. Tabl.: 1. Refs.: 10 titles. Keywords: middleware architecture, geo-distributed middleware architecture, multicloud systems.

Sign in / Sign up

Export Citation Format

Share Document